Rehabilitation Ecology

Rehabilitation Ecology

Ecosystem Structure and Function

There is widespread recognition from all stakeholders of the need for criteria to determine when mine rehabilitation is successful or complete. Irrespective of the agreed post-mining land use, a company must ensure that the rehabilitated land will be sustainable under the climatic context. Mine rehabilitation provides opportunities to create stable, safe and productive systems ranging from agricultural uses to wildlife habitats, with the consequential environmental and social benefits.


Scientifically understanding what constitutes
sustainable ecosystems on mined landscapes
is one of the key areas of activity at CMLR.




Research considers factors that influence seed dormancy and germination, substrate-plant relationships, roles of microbial and faunal assemblages, fire resilience, productivity and biodiversity values. CMLR actively contributes to the development of rehabilitation indicators and completion criteria across a spectrum of sites, utilising new technologies to monitor the effectiveness of rehabilitation programs and the sustainability of the resulting rehabilitated ecosystems.

Monitoring and Mapping Technologies

Gaining confidence in the success of mine site rehabilitation requires assessment of a range of spatially explicit parameters such as grass cover, tree density, biodiversity, growth rates, natural recruitment, salinity and erosion. Using remote sensing techniques, mine sites might be monitored at temporal and spatial sampling intensities that adequately identify changes in ecosystems, and in hydrological and landform processes over time, with a high degree of confidence.


The CMLR conducts research using remote sensing technologies and is developing spatial analysis methods for mapping and monitoring mined sites for rehabilitation. Areas of specialisation include using thermal, near-infrared and true colour sensors on a UAV platform.



The assessment of long-term change in mine site condition using satellite based remote sensing data is also being studied. The goal of this research is to develop spatially based, statistical methods of correlating spatial data and ground observations with specified outcomes and rehabilitation management actions.